4 citations · 6 across the 5 of their papers we have counts for
5 papers
Solving Stochastic Optimization with Expectation Constraints Efficiently by a Stochastic Augmented Lagrangian-Type Algorithm
Liwei Zhang, Yule Zhang, Jia Wu +1
This paper considers the problem of minimizing a convex expectation function with a set of inequality convex expectation constraints. We present a computable stochastic approximati…
Stochastic Approximation Proximal Method of Multipliers for Convex Stochastic Programming
Liwei Zhang, Yule Zhang, Jia Wu
This paper considers the problem of minimizing a convex expectation function over a closed convex set, coupled with a set of inequality convex expectation constraints. We present a…
Online Alternating Direction Method of Multipliers for Online Composite Optimization
Yule Zhang, Zehao Xiao, Jia Wu +1
In this paper, we investigate regrets of an online semi-proximal alternating direction method of multiplier (Online-spADMM) for solving online linearly constrained convex composite…
The Rate of Convergence of the Augmented Lagrangian Method for a Nonlinear Semidefinite Nuclear Norm Composite Optimization Problem
Liwei Zhang, Yule Zhang, Jia Wu
We propose two basic assumptions, under which the rate of convergence of the augmented Lagrange method for a class of composite optimization problems is estimated. We analyze the r…
A Linearly Convergent Majorized ADMM with Indefinite Proximal Terms for Convex Composite Programming and Its Applications
Ning Zhang, Jia Wu, Liwei Zhang
This paper aims to study a majorized alternating direction method of multipliers with indefinite proximal terms (iPADMM) for convex composite optimization problems. We show that th…